CHANGDE CHENG LAB
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Changde Cheng Lab

Computational Biology and Cancer Genomics

We investigate the impact of (epi-)mutations and cell-cell communication in cancer genomics using computational and analytical methods. We develop innovative analytical methods and machine-learning tools to advance our understanding of cancer biology in patients. We take high-throughput approaches, including single-cell RNA-seq, spatial, multiomics, and perturbation sequencing, to study cancer’s origin, progression, and therapeutic resistance. Our research focuses on identifying the cancer cell subpopulations responsible for relapse and understanding how microenvironments influence their response to treatment by decoding communication networks among cells.

Our ultimate goal is to translate our research findings into clinical settings to improve cancer treatment precision, minimize disease recurrence risk, and enhance patient outcomes.

List of working papers


Sexually antagonistic selection and sex chromosome evolution in Stickleback

Submission to the 2017 Society for Molecular Biology & Evolution meeting at Austin, TX.
Jan 25, 2017
Changde Cheng, Andrius J. Dagilis, Jason M. Sardell, Asano Ishikawa, Jun Kitano, Matthew P. Josephson, Catherine L. Peichel, Mark Kirkpatrick

Innate T cells regulate early inflammation and neurological outcomes after cardiac arrest and resuscitation

Among patients hospitalized for cardiac arrest (CA), most deaths are driven by neurological injury. Despite its clinical importance, there are no effective pharmacological…
Feb 1, 2022

DNA damage response and repair genes and Anthracycline-induced cardiomyopathy in childhood cancer survivors: a report from the Children’s Oncology Group and the Childhood Cancer Survivor Study.

Anthracyclines induce cardiotoxicity via DNA double-strand breaks (DSBs) and reactive oxygen species (ROS) formation, resulting in cardiomyocyte dysfunction. The role of DNA…
Oct 30, 2023
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